The official PyTorch implementation of CVPR 2020 paper "Interactive Image Segmentation with First Click Attention".
- PyTorch>=0.4.1
- Opencv
- Scipy
- Matplotlib
Put the pretrained model into the folder "pretrained_model" and the unzipped datasets into the folder "dataset".
python evaluate.py --backbone [resnet,res2net] --dataset [GrabCut,Berkeley,DAVIS,VOC2012] (--sis)
python annotator.py --backbone [resnet,res2net] --input test.jpg --output test_mask.jpg (--sis)
([x,y,z] means choices. (x) means optional.)
- GrabCut ( GoogleDrive | BaiduYun pwd: 6qkj )
- Berkeley ( GoogleDrive | BaiduYun pwd: 6bfw )
- DAVIS ( GoogleDrive | BaiduYun pwd: u5vd )
(The three datasets we used are downloaded from f-BRS) - PASCAL ( official )
- fcanet-resnet ( GoogleDrive | BaiduYun pwd: g989 )
- fcanet-res2net ( GoogleDrive | BaiduYun pwd: xzmx )
We offer the code in constructed by MindSpore framework.
If you find this work or code is helpful in your research, please cite:
@inproceedings{lin2020fclick,
title={Interactive image segmentation with first click attention},
author={Lin, Zheng and Zhang, Zhao and Chen, Lin-Zhuo and Cheng, Ming-Ming and Lu, Shao-Ping},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={13339--13348},
year={2020}
}
If you have any questions, feel free to contact me via: frazer.linzheng(at)gmail.com
.
Welcome to visit the project page or my home page.
The source code is free for research and education use only. Any comercial use should get formal permission first.